Optical character recognition (OCR) is the process of extracting handwritten or printed text
from a scanned or printed image and converting it to a machine-readable form for further …

In the current industrial landscape, a significant number of sectors are grappling with the
challenges posed by unstructured data, which incurs financial losses amounting to millions …

This paper comprehensively assesses the application of active learning strategies to
enhance natural language processing-based optical character recognition (OCR) models for …

Early fire detection and timely notification are paramount for preventing human and material
casualties caused by fire. As a result, scientists have developed various fire monitoring …

Event of the disastrous scenarios are actively discussed on microblogging platforms like
Twitter which can lead to chaotic situations. In the era of machine learning and deep …

Object detection methods based on deep learning have been used in a variety of sectors
including banking, healthcare, e-governance, and academia. In recent years, there has …

This paper introduces a new method for the region segmentation of images. The approach is
based on the raster-scan paradigm and builds the segments incrementally. The pixels are …

Optical Character Recognition (OCR) is an established task with the objective of identifying
the text present in an image. While many off-the-shelf OCR models exist, they are often …

This paper presents an integrated approach to sentiment analysis of beauty product reviews
using the IndoBERT model combined with Naive Bayes classification, which specifically …

U. Poudel et al. experiments conducted on five different image categories: vehicle number
plates, receipts, handwriting, symbols and plain text images. Evaluation metrics such as …